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The Platonic Representation Hypothesis (PRH) suggests that neural networks are converging toward similar representation spaces.
다른 보도 ADP
This work proposes WaveGen, a fully end-to-end diffusion-based text-to-waveform framework based on Spectral Forcing, which jointly learns an internal spectral…
A sparse terminal reward tells an agent little about its steps. Much of the missing information is implicit in the environment's dynamics, because each state…
다른 보도 The Verge
World models enable agents to plan and learn from imagined experience, but in an unfamiliar environment they must learn its mechanics from limited interaction.
We introduce Sage-Taiyi, a metacognition-inspired architecture that uses accumulated scientific understanding to guide what to investigate next and how to…
Tactile sensing is an indispensable modality for contact-rich dexterous manipulation, a capability that hints at the ultimate frontiers of embodied…
Agentic reinforcement learning (RL) and multi-teacher on-policy distillation (MOPD) offer complementary routes to post-training.
Self-supervised learning in Vision Transformer models, such as DINO, enables robust visual perception without requiring labeled data by leveraging large-scale…
World action models jointly predict video and actions conditioned on language.
Despite impressive progress, existing feed-forward large 3D reconstruction models produce a single, irrevocable prediction.
Many of the most consequential advances promised by AI, from curing diseases and inventing new technologies to formulating new scientific theories, are…
We introduce FraudBench, an evaluation of large language models' (LLMs) propensities to recommend, assist, or directly take actions that would constitute fraud…
In this work, we study whether frontier agent can continually improve real-world AI infrastructure over long horizons.
Small multimodal models can misjudge emotion when words, voice, and visual cues conflict.
Discrete autoregressive modeling, notably through next-token prediction, has become a cornerstone of modern language models.
While modern video generative models achieve remarkable visual fidelity, they remain noticeably brittle when generating physically plausible dynamics and…
Trained action policies write manipulation skill into network weights, tying what is learned to the distribution it is learned from.
Protein engineering requires navigating rugged fitness landscapes, where small sequence changes can produce large functional differences, but experimental…
Reinforcement learning (RL) can improve an agent's task capability while reinforcing behavior that violates contextual execution requirements.
Scientific discovery requires ideas that are original, useful, and non-obvious.
Early successes on agentic robotics point to a potential paradigm shift toward using coding agents to control robots.
LiDAR point clouds and 3D semantic occupancy represent two distinct modalities capturing fine-grained metric geometry and dense volumetric semantics…
AAA games offer a rich testbed for evaluating agent perception, reasoning, and control.
Agentic workloads are a major source of LLM inference demand. Existing prefill--decode (PD) disaggregated serving systems offer limited flexibility for runtime…
As multimodal agents accumulate increasingly long interaction histories, effectively retrieving and utilizing past information becomes critical for long-term…
While Recursive Self-Improvement (RSI) accelerates isolated algorithm and kernel synthesis, distributed LLM training depends on tightly coupled launch…
On-policy distillation (OPD) trains a student language model on its own responses, guided by a fixed teacher.
Spatial reasoning requires understanding how objects and observers are arranged in a scene and how their relations change with viewpoint or movement.
Generation, imputation, and prediction query different aspects of the same tabular distribution, but are usually evaluated separately.
Which representation should be probed in a transformer-based foundation model?
Discrete autoregressive models offer a scalable framework for image generation.